Transcription of Data Mining: Practical Machine Learning Tools and ...
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Data Mining: Practical Machine Learning Tools and ...
Data MiningPractical Machine Learning Tools and 5/3/05 2:21 PM Page iThe Morgan Kaufmann Series in Data Management SystemsSeries Editor:Jim Gray, Microsoft ResearchData Mining: Practical Machine LearningTools and Techniques, Second EditionIan H. Witten and Eibe FrankFuzzy Modeling and Genetic Algorithms forData Mining and ExplorationEarl CoxData Modeling Essentials, Third EditionGraeme C. Simsion and Graham C. WittLocation-Based ServicesJochen Schiller and Agn s VoisardDatabase Modeling with Microsoft Visio forEnterprise ArchitectsTerry Halpin, Ken Evans, Patrick Hallock,and Bill MacleanDesigning Data-Intensive Web ApplicationsStefano Ceri, Piero Fraternali, Aldo Bongio,Marco Brambilla, Sara Comai, andMaristella MateraMining the Web: Discovering Knowledgefrom Hypertext DataSoumen ChakrabartiAdvanced SQL: 1999 UnderstandingObject-Relational and Other AdvancedFeaturesJim MeltonDatabase Tuning: Principles, Experiments,and Troubleshooting TechniquesDennis Shasha and Philippe BonnetSQL: 1999 Understanding RelationalLanguage ComponentsJim Melton and Alan R.
They present the basic theory of automatically extracting models from data, and then validating those models.The book does an excellent job of explaining the various models (decision trees, association rules, linear models, clustering, Bayes nets,neural nets) and how to apply them in practice.With this basis,they
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